A SCADA control method and system for producing natural gas from biogas based on temperature and pressure balance

Abstract

The invention discloses a SCADA control method and system for biogas-to-natural gas based on temperature and pressure balance, which relates to the field of intelligent control technology, including: installing high-precision temperature sensors and pressure sensors on a biomass biogas-to-natural gas process device to obtain temperature and pressure balance parameters in real time, and removing noise and abnormal values ​​through a data cleaning algorithm; using a linear regression model to capture the linear relationship between temperature and pressure, and using an adaptive learning model to capture the nonlinear relationship between temperature and pressure; constructing and adjusting a temperature and pressure balance model in real time based on the outputs of the linear regression model and the adaptive learning model in combination with a logistic regression model, inputting the real-time collected temperature and pressure into the temperature and pressure balance model, predicting the optimal temperature and pressure setting values ​​under the current environment according to the model, and adjusting the working states of a heater, a cooler and a pressure regulating valve through the optimal temperature and pressure setting values ​​by a control module.

Description

Technical Field

[0001] The invention relates to the field of intelligent control technology, in particular to a SCADA control method and system for producing natural gas from biogas based on temperature and pressure balance. Background Art

[0002] Biogas comes from the anaerobic fermentation of biomass waste, and can be converted into methane with high added value through a series of chemical reactions, which can not only reduce greenhouse gas emissions, but also realize energy recycling. In order to improve the efficiency of biogas-to-natural gas process, traditional control systems usually rely on simple temperature and pressure monitoring. However, this monitoring method cannot effectively cope with complex process condition changes, especially when the temperature and pressure fluctuate greatly. The system is prone to control lag or inaccurate adjustment, which in turn affects the stability of the production process and energy utilization efficiency. In recent years, with the advancement of automation control technology, SCADA data acquisition and monitoring system technology has been widely used in the monitoring and management of biogas-to-natural gas process. The SCADA system can effectively realize the automation control of the process flow by real-time acquisition, processing and feedback of temperature and pressure physical parameters. However, when dealing with complex temperature and pressure dynamic balance problems, the existing SCADA system still has room for optimization;

[0003] The existing SCADA control technology for biogas to natural gas has the following main shortcomings. First, most traditional control methods use simple linear control models, ignoring the nonlinear coupling relationship between temperature and pressure, resulting in insufficient response or delayed adjustment of the control strategy when facing complex process conditions. At the same time, the existing system generally lacks accurate modeling of the balance relationship between temperature and pressure parameters. The feedback control strategy of the system is often difficult to achieve optimal control under multivariable conditions, resulting in energy waste and reduced production efficiency. In addition, the current control system is not good at responding to abnormal working conditions, and it is difficult to achieve real-time monitoring and early warning of temperature and pressure status, especially when the dynamic fluctuations of temperature and pressure exceed the preset range, it is often impossible to respond in time, thereby causing potential safety hazards. Therefore, the existing technology requires a refined control method that can fully consider the coupling relationship between temperature and pressure, combined with advanced artificial intelligence technology to improve the adaptability and control accuracy to complex process conditions. Summary of the invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a SCADA control method and system for biogas to natural gas based on temperature and pressure balance to solve the problem that most traditional control methods adopt a simple linear control model, ignoring the nonlinear coupling relationship between temperature and pressure, resulting in insufficient response or delayed adjustment of the control strategy when facing complex process conditions.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, an embodiment of the present invention provides a SCADA control method for producing natural gas from biogas based on temperature and pressure balance, which comprises:

[0008] Install high-precision temperature sensors and pressure sensors on the biogas-to-natural gas process unit to obtain temperature and pressure balance parameters in real time, and remove noise and outliers through data cleaning algorithms;

[0009] A linear regression model is used to capture the linear relationship between temperature and pressure, and an adaptive learning model is used to capture the nonlinear relationship between temperature and pressure;

[0010] According to the output of the linear regression model and the adaptive learning model, the temperature and pressure balance model is constructed and adjusted in real time in combination with the logistic regression model. The real-time collected temperature and pressure are input into the temperature and pressure balance model. The optimal temperature and pressure setting values ​​under the current environment are predicted according to the model. The control module adjusts the working states of the heater, cooler and pressure regulating valve according to the optimal temperature and pressure setting values.

[0011] Define the pressure difference between the pressure gauges and set the threshold. When the internal temperature and pressure conditions exceed the set threshold, the alarm is triggered and the event log is recorded. Depending on the severity of the abnormal situation, the corresponding emergency measures are automatically initiated.

[0012] As a preferred solution of the SCADA control method for producing natural gas from biogas based on temperature and pressure balance of the present invention, wherein: a high-precision temperature sensor and a pressure sensor are installed on the biomass biogas to natural gas process device to obtain temperature and pressure balance parameters in real time, and the specific steps are as follows:

[0013] A temperature sensor and a pressure sensor are installed at the feed inlet of the biogas-to-natural gas process to collect the temperature and pressure of the biogas respectively;

[0014] Set the initial temperature and pressure balance parameters, that is, set the target temperature range to arrive ,in, Indicates the target minimum temperature, Indicates the target maximum temperature and the target pressure range is arrive , Indicates the target minimum pressure, Indicates the target maximum pressure;

[0015] Calculate temperature and pressure balance parameters, i.e., initial target temperature and initial target pressure, according to the target temperature range and the target pressure range;

[0016] A control module is installed in the SCADA host in the central control room, the initial target temperature and the initial target pressure are set in the control module, and the working states of the heater, cooler and pressure regulating valve are adjusted according to the set temperature and pressure balance parameters.

[0017] As a preferred solution of the SCADA control method for producing natural gas from biogas based on temperature and pressure balance of the present invention, wherein: the noise and abnormal values ​​are removed by the data cleaning algorithm, and the specific steps are as follows:

[0018] Set the acquisition frequency to regularly read temperature and pressure data from each sensor and transmit it to the SCADA host in the central control room;

[0019] Configure the database in the SCADA host and store the collected temperature and pressure data according to the timestamp in the database;

[0020] Use data cleaning algorithms to remove noise and outliers from collected data;

[0021] Then the cleaned data is standardized to obtain the standardized temperature and pressure .

[0022] As a preferred solution of the SCADA control method for producing natural gas from biogas based on temperature and pressure balance of the present invention, wherein: the linear regression model is used to capture the linear relationship between temperature and pressure, and the adaptive learning model is used to capture the nonlinear relationship between temperature and pressure. The specific steps are:

[0023] The linear relationship between temperature and pressure is expressed as:

[0024] ;

[0025] in, represents the output of the linear regression model, i.e., the linear relationship between temperature and pressure, is the bias term, and represents the regression coefficients of temperature and pressure, and Shows standardized temperature and pressure;

[0026] The adaptive learning model uses a multi-layer perceptron structure, and its output is expressed as:

[0027] ;

[0028] in, represents the output of the adaptive learning model, i.e., the nonlinear relationship between temperature and pressure, represents the weight matrix of the adaptive learning model, represents the bias vector, Represents the activation function Sigmoid function.

[0029] As a preferred solution of the SCADA control method for producing natural gas from biogas based on temperature and pressure balance described in the present invention, wherein: the output of the linear regression model and the adaptive learning model is combined with the logistic regression model to construct and adjust the temperature and pressure balance model in real time, the real-time collected temperature and pressure are input into the temperature and pressure balance model, and the optimal temperature and pressure setting values ​​under the current environment are predicted according to the model. The control module adjusts the working states of the heater, cooler and pressure regulating valve according to the optimal temperature and pressure setting values. The specific steps are as follows:

[0030] The logistic regression model is used as the basis of the temperature-pressure balance model. The final temperature-pressure balance value is predicted based on the output of the linear regression model and the output of the adaptive learning model. The expression of the temperature-pressure balance model is:

[0031] ;

[0032] in, represents the final predicted temperature-pressure balance value, is the bias term, and Respectively and The weight of Represents the base of the exponential function;

[0033] According to the final predicted temperature and pressure balance value The optimal temperature and pressure setting values ​​under the current environment are calculated and expressed as:

[0034] ;

[0035] ;

[0036] in, represents the optimal temperature setting value, Indicates the optimal pressure setting value;

[0037] The optimal temperature setting value and optimal pressure setting Sent to the control module, which makes real-time adjustments to the heater, cooler and pressure regulating valve.

[0038] As a preferred solution of the SCADA control method for producing natural gas from biogas based on temperature and pressure balance of the present invention, wherein: the pressure difference between the pressure gauges is defined, a threshold is set, and when the internal temperature and pressure state exceeds the set threshold, an alarm is immediately triggered and an event log is recorded. The specific steps are:

[0039] The pressure is collected through three pressure sensors installed at the feed inlet;

[0040] Set the pressure values ​​collected by the three pressure sensors to be , and ;

[0041] According to the pressure value , and , calculate the pressure difference between each pressure gauge, the expression is:

[0042] ;

[0043] ;

[0044] ;

[0045] ;

[0046] ;

[0047] ;

[0048] in, , and Respectively represent the pressure values ​​of the pressure sensors at the three positions of the feed inlet, and express and The absolute pressure difference between them is equal to the calculated value. and express and The absolute pressure difference between them is equal to the calculated value. and express and The absolute pressure difference between them is equal to the calculated value.

[0049] Set the threshold of each pressure difference to ;

[0050] Under normal operating conditions, the pressure difference between the two pressure sensor locations will not exceed this threshold;

[0051] When the pressure difference between any two pressure sensor positions exceeds or equals the threshold, it is judged as abnormal.

[0052] As a preferred solution of the SCADA control method for producing natural gas from biogas based on temperature and pressure balance of the present invention, the corresponding emergency measures are automatically initiated according to the severity of the abnormal situation, specifically,

[0053] when and The value is greater than or equal to When the pressure value is There is a problem with the pressure sensor. When it is judged as abnormal, only use and The average pressure is calculated from the data;

[0054] when and The value is greater than or equal to When the pressure value is There is a problem with the pressure sensor. When it is judged as abnormal, only use and The average pressure is calculated from the data;

[0055] when and The value is greater than or equal to When the pressure value is There is a problem with the pressure sensor. When it is judged as abnormal, only use and The average pressure is calculated from the data;

[0056] The remaining sensor data is input into the temperature and pressure balance model to obtain the final temperature and pressure balance value, and the optimal temperature setting value and the optimal pressure setting value under the current environment are calculated according to the final temperature and pressure balance value;

[0057] When the absolute pressure difference of each pressure gauge is greater than or equal to When the prediction result of the temperature and pressure balance model shows that the current temperature and pressure status is abnormal, an alarm will be triggered immediately and the event log will be recorded in the SCADA;

[0058] Collect real-time data, clean and standardize the real-time data, and calculate the pressure difference to obtain the real-time pressure difference. , according to the real-time pressure difference and the threshold value for each pressure difference Calculate the deviation ratio;

[0059] Set the deviation thresholds T1, T2 and T3, T1 <T2<T3;

[0060] When T1<deviation ratio≤T2, it is judged as a slight abnormality;

[0061] When T2<deviation ratio≤T3, it is judged as moderate abnormality;

[0062] When T3<deviation ratio, it is judged as a serious abnormality.

[0063] In a second aspect, the present invention provides a SCADA control system for producing natural gas from biogas based on temperature and pressure balance, comprising a sensor module, a data processing module, a temperature and pressure balance model module, a control module and an abnormality detection module.

[0064] The sensor module is used to monitor the temperature and pressure data in the biogas to natural gas process in real time through a temperature sensor and a pressure sensor;

[0065] The data processing module is used to clean and standardize the collected temperature and pressure data, and also calculate the real-time pressure difference and compare it with the set threshold value;

[0066] The temperature and pressure balance model module includes a linear regression model and an adaptive learning model, which respectively capture the linear and nonlinear relationships between temperature and pressure, and are used to combine the output of the model with the logistic regression model to construct a temperature and pressure balance model, predict the optimal temperature and pressure setting values ​​under the current environment, and calculate the optimal temperature setting value and pressure setting value according to the final predicted value;

[0067] The control module is used to adjust the working states of the heater, cooler and pressure regulating valve in real time according to the predicted output of the temperature-pressure balance model;

[0068] The anomaly detection module is used to monitor the temperature and pressure status of the system, define the pressure difference between the pressure sensors and set the threshold. When the system exceeds the set threshold, an alarm is triggered and an event log is recorded. Emergency measures are automatically taken according to the severity of the anomaly.

[0069] In a third aspect, an embodiment of the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, any step of the SCADA control method for producing natural gas from biogas based on temperature and pressure balance as described in the first aspect of the present invention is implemented.

[0070] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, any step of the SCADA control method for producing natural gas from biogas based on temperature and pressure balance as described in the first aspect of the present invention is implemented.

[0071] The beneficial effects of the present invention are as follows: the present invention installs high-precision temperature and pressure sensors, collects and cleans temperature and pressure data in real time, combines linear regression with adaptive learning models, and constructs an accurate temperature and pressure balance model. The model can capture the linear and nonlinear relationship between temperature and pressure, and is further optimized through logistic regression to predict the optimal temperature and pressure setting values. The system automatically adjusts the heater, cooler and pressure regulating valve according to the prediction results to achieve precise control of temperature and pressure, ensuring the stable operation of the biogas-to-natural gas process in a dynamic environment. In addition, the system can detect abnormal conditions in time through pressure difference monitoring and setting thresholds, automatically trigger emergency responses, and take different processing measures according to the severity of the abnormality, thereby ensuring the safety and reliability of the system. Even in the event of individual sensor failures, the system can maintain normal operation through data correction, demonstrating strong fault tolerance. Overall, the invention improves the automation and intelligence level of the biogas-to-natural gas process, and significantly improves energy utilization efficiency and system safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0073] Figure 1 This is a flow chart of the SCADA control method for producing natural gas from biogas based on temperature and pressure balance in Example 1.

[0074] Figure 2 This is a flow chart of the optimal temperature setting value and the optimal pressure setting value under the current environment in Example 1.

[0075] Figure 3 This is an interval diagram of system abnormality in Example 1. DETAILED DESCRIPTION

[0076] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0077] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0078] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0079] Example 1, reference Figure 1~Figure 3 , which is the first embodiment of the present invention, provides a SCADA control method for producing natural gas from biogas based on temperature and pressure balance, comprising the following steps:

[0080] S1. Install high-precision temperature sensors and pressure sensors on the biogas-to-natural gas process device to obtain temperature and pressure balance parameters in real time, and remove noise and outliers through data cleaning algorithms;

[0081] A temperature sensor and a pressure sensor are installed at the feed inlet of the biogas-to-natural gas process to collect the temperature and pressure of the biogas respectively;

[0082] Set the initial temperature and pressure balance parameters, that is, set the target temperature range to arrive ,in, Indicates the target minimum temperature, Indicates the target maximum temperature and the target pressure range is arrive , Indicates the target minimum pressure, Indicates the target maximum pressure;

[0083] The temperature and pressure balance parameters, namely the initial target temperature and the initial target pressure, are calculated according to the target temperature range and the target pressure range. The expression is:

[0084] ;

[0085] ;

[0086] in, represents the initial target temperature, represents the initial target pressure, and represent the temperature correction factor and the pressure correction factor respectively, Indicates the temperature deviation, which is obtained by subtracting the temperature at the midpoint of the target temperature range from the current ambient temperature. Indicates the pressure deviation, which is obtained by subtracting the pressure at the midpoint of the target pressure range from the current ambient pressure;

[0087] Install a control module in the SCADA host in the central control room, set the initial target temperature and initial target pressure in the control module, and adjust the working states of the heater, cooler and pressure regulating valve according to the set temperature and pressure balance parameters;

[0088] Adjusting the working state of the heater, cooler and pressure regulating valve according to the set temperature and pressure balance parameters means:

[0089] For a heater, when the target temperature of the heater is lower than the current temperature, the power of the heater is reduced or the heater is turned off to lower the temperature;

[0090] When the target temperature of the heater is higher than the current temperature, the power of the heater is increased to increase the temperature;

[0091] For a cooler, when the target temperature of the cooler is lower than the current temperature, the power of the cooler is increased to reduce the temperature;

[0092] When the target temperature of the cooler is higher than the current temperature, the power of the cooler is reduced or the cooler is turned off to prevent the temperature from being too low;

[0093] For the pressure regulating valve, when the target pressure of the pressure regulating valve is lower than the current pressure, the pressure regulating valve is opened to release the excess pressure;

[0094] When the target pressure of the pressure regulating valve is higher than the current pressure, the pressure regulating valve is closed to increase the pressure of the SCADA host.

[0095] S2, using a linear regression model to capture the linear relationship between temperature and pressure, and using an adaptive learning model to capture the nonlinear relationship between temperature and pressure;

[0096] Set the acquisition frequency to regularly read temperature and pressure data from each sensor and transmit it to the SCADA host in the central control room;

[0097] Configure the database in the SCADA host and store the collected temperature and pressure data according to the timestamp in the database to ensure the traceability and integrity of the data;

[0098] Use the data cleaning algorithm to remove noise and outliers in the collected data. The data cleaning formula is:

[0099] ;

[0100] ;

[0101] in, Indicates the temperature after cleaning, Represents the original temperature, that is, the temperature value directly collected by the sensor. represents the average temperature, represents the standard deviation of temperature, Indicates the pressure after cleaning, that is, the pressure value directly collected by the sensor. represents the original pressure, represents the average pressure, represents the standard deviation of pressure;

[0102] Then the cleaned data is standardized to obtain the standardized temperature and pressure .

[0103] S3 constructs and adjusts the temperature and pressure balance model in real time based on the output of the linear regression model and the adaptive learning model combined with the logistic regression model, inputs the real-time collected temperature and pressure into the temperature and pressure balance model, and predicts the optimal temperature and pressure setting values ​​under the current environment based on the model. The control module adjusts the working states of the heater, cooler and pressure regulating valve according to the optimal temperature and pressure setting values;

[0104] The linear relationship between temperature and pressure is expressed as:

[0105] ;

[0106] in, represents the output of the linear regression model, i.e., the linear relationship between temperature and pressure, is the bias term, and represents the regression coefficients of temperature and pressure, and Shows standardized temperature and pressure;

[0107] The adaptive learning model uses a multi-layer perceptron structure, which includes an input layer, a hidden layer, and an output layer. Its output is expressed as:

[0108] ;

[0109] in, represents the output of the adaptive learning model, i.e., the nonlinear relationship between temperature and pressure, represents the weight matrix of the adaptive learning model, represents the bias vector, Represents the activation function Sigmoid function;

[0110] The present invention combines linear regression with an adaptive learning model, using the former to capture linear trends in data and the latter to identify and model nonlinear characteristics in data. This combination not only fully utilizes the advantages of both models, but also effectively overcomes the limitations that a single model may have in specific scenarios.

[0111] By combining the linear regression model with the adaptive learning model to capture the linear and nonlinear relationship between temperature and pressure, it aims to provide a more accurate and comprehensive prediction method. This method can not only effectively improve the prediction accuracy, but also better adapt to the complex changes in different environments, providing strong support for the fields of industrial process control and environmental monitoring.

[0112] In order to combine the output of linear regression and neural network, the logistic regression model is used as the basis of the temperature-pressure balance model. The final temperature-pressure balance value is predicted according to the output of the linear regression model and the output of the adaptive learning model. The expression of the temperature-pressure balance model is:

[0113] ;

[0114] in, represents the final predicted temperature-pressure balance value, is the bias term, and Respectively and The weight of Represents the base of the exponential function;

[0115] According to the final predicted temperature and pressure balance value The optimal temperature and pressure setting values ​​under the current environment are calculated and expressed as:

[0116] ;

[0117] ;

[0118] in, represents the optimal temperature setting value, Indicates the optimal pressure setting value;

[0119] The optimal temperature setting value and optimal pressure setting Send to the control module, through which the heater, cooler and pressure regulating valve are adjusted in real time;

[0120] For heaters, when the heater Increase the heater power at the current temperature, otherwise reduce the heater power or turn off the heater;

[0121] For the cooler, when the cooler When the temperature is lower than the current temperature, the cooler power is increased; otherwise, the cooler power is reduced or the cooler is turned off;

[0122] For the pressure regulating valve, when the target pressure of the pressure regulating valve is lower than the current pressure, the pressure regulating valve is opened to release the excess pressure;

[0123] When the pressure regulating valve When the pressure is higher than the current pressure, close the valve to increase the pressure, otherwise open the valve to release the pressure.

[0124] S4. Define the pressure difference between the pressure gauges and set the threshold. When the internal temperature and pressure state exceeds the set threshold, the alarm is immediately triggered and the event log is recorded; according to the severity of the abnormal situation, the corresponding emergency measures are automatically initiated;

[0125] The pressure is collected through three pressure sensors installed at the feed inlet;

[0126] Set the pressure values ​​collected by the three pressure sensors to be , and ;

[0127] According to the pressure value , and , calculate the pressure difference between each pressure gauge, the expression is:

[0128] ;

[0129] ;

[0130] ;

[0131] ;

[0132] ;

[0133] ;

[0134] in, , and Respectively represent the pressure sensors at three positions of the feed inlet, and express and The absolute pressure difference between them is equal to the calculated value. and express and The absolute pressure difference between them is equal to the calculated value. and express and The absolute pressure difference between them is equal to the calculated value.

[0135] Set the threshold of each pressure difference to ;

[0136] Under normal operating conditions, the pressure difference between the two pressure sensor locations will not exceed this threshold;

[0137] When the pressure difference between any two pressure sensor positions exceeds or equals the threshold, it is judged as abnormal;

[0138] when and The value is greater than or equal to When the pressure value is There is a problem with the pressure sensor. When it is judged as abnormal, only use and The data is used to calculate the average pressure, and the SCADA host will ignore it. to avoid affecting the calculation of the temperature and pressure balance model;

[0139] when and The value is greater than or equal to When the pressure value is There is a problem with the pressure sensor. When it is judged as abnormal, only use and The data is used to calculate the average pressure, and the SCADA host will ignore it. to avoid affecting the calculation of the temperature and pressure balance model;

[0140] when and The value is greater than or equal to When the pressure value is There is a problem with the pressure sensor. When it is judged as abnormal, only use and The data is used to calculate the average pressure, and the SCADA host will ignore it. to avoid affecting the calculation of the temperature and pressure balance model;

[0141] The remaining sensor data is input into the temperature and pressure balance model, which combines the output of linear regression and neural network to obtain the final temperature and pressure balance value, and the optimal temperature setting value and the optimal pressure setting value under the current environment are calculated according to the final temperature and pressure balance value;

[0142] When the absolute pressure difference of each pressure gauge is greater than or equal to When the prediction result of the temperature and pressure balance model shows that the current temperature and pressure status is abnormal, an alarm will be triggered immediately and the event log will be recorded in the SCADA;

[0143] The event log contains the timestamp of the anomaly, the sensor value at the specific location, the pressure difference, and the deviation value of the current temperature and pressure;

[0144] Collect real-time data, clean and standardize the real-time data, and calculate the pressure difference to obtain the real-time pressure difference. , according to the real-time pressure difference and the threshold value for each pressure difference Calculate the deviation ratio, the expression is:

[0145] ;

[0146] Set the deviation thresholds T1, T2 and T3, T1 <T2<T3;

[0147] When T1<deviation ratio≤T2, it is judged as a slight abnormality, indicating that the current pressure difference slightly exceeds the set normal range, but has not reached a dangerous level. The heater power is reduced and the cooler load is reduced to prevent the temperature and pressure from continuing to rise;

[0148] When T2<deviation ratio≤T3, it is judged as moderate abnormality, indicating that the current pressure difference is slightly outside the normal range and is already in an unsafe state. It is necessary to shut down some heaters and open some pressure regulating valves to release excess pressure and avoid further deterioration.

[0149] When T3 < deviation ratio, it is judged as a serious abnormality, indicating that the pressure difference seriously exceeds the set threshold, which will cause loss of control or equipment damage. It is necessary to completely shut down the heater and open all pressure regulating valves to quickly reduce the internal pressure of the system, issue an emergency alarm, and automatically trigger the shutdown procedure to prevent damage to the equipment and environment. At the same time, the emergency response team is notified and requires immediate manual intervention measures.

[0150] This embodiment also provides a SCADA control system for producing natural gas from biogas based on temperature and pressure balance, including: a sensor module, a data processing module, a temperature and pressure balance model module, a control module and an abnormality detection module.

[0151] The sensor module uses temperature sensors and pressure sensors to monitor the temperature and pressure data in the biogas-to-natural gas process in real time;

[0152] The data processing module is used to clean and standardize the collected temperature and pressure data, and also includes calculating the real-time pressure difference and comparing it with the set threshold value;

[0153] The temperature and pressure balance model module includes a linear regression model and an adaptive learning model, which capture the linear and nonlinear relationships between temperature and pressure respectively. It is used to combine the output of the model with the logistic regression model to construct a temperature and pressure balance model, predict the optimal temperature and pressure setting values ​​under the current environment, and calculate the optimal temperature setting value and pressure setting value based on the final predicted value;

[0154] A control module, used to adjust the working states of the heater, cooler and pressure regulating valve in real time according to the predicted output of the temperature and pressure balance model;

[0155] The anomaly detection module is used to monitor the temperature and pressure status of the system, define the pressure difference between the pressure sensors and set the threshold. When the system exceeds the set threshold, an alarm is triggered and an event log is recorded. Emergency measures are automatically taken according to the severity of the abnormal situation.

[0156] This embodiment also provides a computer device, which is suitable for the SCADA control method of producing natural gas from biogas based on temperature and pressure balance, including: a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the SCADA control method of producing natural gas from biogas based on temperature and pressure balance proposed in the above embodiment.

[0157] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covered on the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0158] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the SCADA control method for producing natural gas from biogas based on temperature and pressure balance proposed in the above embodiment is implemented; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, disk or optical disk.

[0159] In summary, the present invention installs high-precision temperature and pressure sensors, collects and cleans temperature and pressure data in real time, combines linear regression with adaptive learning models, and constructs an accurate temperature and pressure balance model. The model can capture the linear and nonlinear relationship between temperature and pressure, and is further optimized through logistic regression to predict the optimal temperature and pressure setting values. The system automatically adjusts the heater, cooler and pressure regulating valve according to the prediction results to achieve precise control of temperature and pressure, ensuring the stable operation of the biogas-to-natural gas process in a dynamic environment. In addition, the system can detect abnormal conditions in time through pressure difference monitoring and setting thresholds, automatically trigger emergency responses, and take different processing measures according to the severity of the abnormality, thereby ensuring the safety and reliability of the system. Even in the event of individual sensor failures, the system can maintain normal operation through data correction, demonstrating strong fault tolerance. Overall, the invention improves the automation and intelligence level of the biogas-to-natural gas process, and significantly improves energy utilization efficiency and system safety.

[0160] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A SCADA control method for producing natural gas from biogas based on temperature and pressure balance, characterized in that: include, Install high-precision temperature sensors and pressure sensors on the biogas-to-natural gas process unit to obtain temperature and pressure balance parameters in real time, and remove noise and outliers through data cleaning algorithms; A linear regression model is used to capture the linear relationship between temperature and pressure, and an adaptive learning model is used to capture the nonlinear relationship between temperature and pressure; According to the output of the linear regression model and the adaptive learning model, the temperature and pressure balance model is constructed and adjusted in real time in combination with the logistic regression model. The real-time collected temperature and pressure are input into the temperature and pressure balance model. The optimal temperature and pressure setting values ​​under the current environment are predicted according to the model. The control module adjusts the working states of the heater, cooler and pressure regulating valve according to the optimal temperature and pressure setting values. Define the pressure difference between the pressure gauges and set the threshold. When the internal temperature and pressure state exceeds the set threshold, the alarm is triggered and the event log is recorded. According to the severity of the abnormal situation, the corresponding emergency measures are automatically initiated. The linear regression model is used to capture the linear relationship between temperature and pressure, and the adaptive learning model is used to capture the nonlinear relationship between temperature and pressure. The specific steps are: The linear relationship between temperature and pressure is expressed as: ； in, represents the output of the linear regression model, i.e., the linear relationship between temperature and pressure, is the bias term, and represents the regression coefficients of temperature and pressure, and Shows standardized temperature and pressure; The adaptive learning model uses a multi-layer perceptron structure, and its output is expressed as: ； in, represents the output of the adaptive learning model, i.e., the nonlinear relationship between temperature and pressure, represents the weight matrix of the adaptive learning model, represents the bias vector, Represents the activation function Sigmoid function; The output of the linear regression model and the adaptive learning model is combined with the logistic regression model to build and adjust the temperature and pressure balance model in real time, the real-time collected temperature and pressure are input into the temperature and pressure balance model, and the optimal temperature and pressure setting values ​​under the current environment are predicted according to the model. The control module adjusts the working states of the heater, cooler and pressure regulating valve according to the optimal temperature and pressure setting values. The specific steps are as follows: The logistic regression model is used as the basis of the temperature-pressure balance model. The final temperature-pressure balance value is predicted based on the output of the linear regression model and the output of the adaptive learning model. The expression of the temperature-pressure balance model is: ； in, represents the final predicted temperature-pressure balance value, is the bias term, and Respectively and The weight of Represents the base of the exponential function; According to the final predicted temperature and pressure balance value The optimal temperature and pressure setting values ​​under the current environment are calculated and expressed as: ； ； in, represents the optimal temperature setting value, Indicates the optimal pressure setting value; The optimal temperature setting value and optimal pressure setting Sent to the control module, which makes real-time adjustments to the heater, cooler and pressure regulating valve.

2. The SCADA control method for producing natural gas from biogas based on temperature and pressure balance according to claim 1, characterized in that: The high-precision temperature sensor and pressure sensor are installed on the biomass biogas to natural gas process device to obtain temperature and pressure balance parameters in real time. The specific steps are: Temperature sensors and pressure sensors are installed at the feed inlet, reactor and compressor of the biogas-to-natural gas process to collect the temperature and pressure of the biogas respectively; Set the initial temperature and pressure balance parameters, that is, set the target temperature range to arrive ,in, Indicates the target minimum temperature, Indicates the target maximum temperature and the target pressure range is arrive , Indicates the target minimum pressure, Indicates the target maximum pressure; Calculate temperature and pressure balance parameters, i.e., initial target temperature and initial target pressure, according to the target temperature range and the target pressure range; A control module is installed in the SCADA host in the central control room, the initial target temperature and the initial target pressure are set in the control module, and the working states of the heater, cooler and pressure regulating valve are adjusted according to the set temperature and pressure balance parameters.

3. The SCADA control method for producing natural gas from biogas based on temperature and pressure balance according to claim 2, characterized in that: The data cleaning algorithm is used to remove noise and outliers. The specific steps are: Set the acquisition frequency to regularly read temperature and pressure data from each sensor and transmit it to the SCADA host in the central control room; Configure the database in the SCADA host and store the collected temperature and pressure data according to the timestamp in the database; Use data cleaning algorithms to remove noise and outliers from collected data; Then the cleaned data is standardized to obtain the standardized temperature and pressure .

4. The SCADA control method for producing natural gas from biogas based on temperature and pressure balance according to claim 3, characterized in that: The pressure difference between the pressure gauges is defined, and a threshold is set. When the internal temperature and pressure state exceeds the set threshold, an alarm is immediately triggered and an event log is recorded. The specific steps are: The pressure was collected by three pressure sensors installed at the feed inlet, reactor, and compressor locations; Set the pressure values ​​collected by the three pressure sensors to be , and ; According to the pressure value , and , calculate the pressure difference between each pressure gauge, the expression is: ； ； ； ； ； ； in, , and Respectively represent the pressure values ​​of the pressure sensors at the feed inlet, reactor and compressor. and express and The absolute pressure difference between them is equal to and express and The absolute pressure difference between them is equal to and express and The absolute pressure difference between them is equal to the calculated value. Set the threshold of each pressure difference to ; Under normal operating conditions, the pressure difference between the two pressure sensor locations will not exceed this threshold; When the pressure difference between any two pressure sensor positions exceeds or equals the threshold, it is judged as abnormal.

5. The SCADA control method for producing natural gas from biogas based on temperature and pressure balance according to claim 4, characterized in that: According to the severity of the abnormal situation, the corresponding emergency measures are automatically initiated, specifically, when and The value is greater than or equal to When the pressure value is There is a problem with the pressure sensor. When it is judged as abnormal, only use and The average value of pressure is calculated from the data; when and The value is greater than or equal to When the pressure value is There is a problem with the pressure sensor. When it is judged as abnormal, only use and The average value of pressure is calculated from the data; when and The value is greater than or equal to When the pressure value is There is a problem with the pressure sensor. When it is judged as abnormal, only use and The average value of pressure is calculated from the data; The remaining sensor data is input into the temperature and pressure balance model to obtain the final temperature and pressure balance value, and the optimal temperature setting value and the optimal pressure setting value under the current environment are calculated according to the final temperature and pressure balance value; When the absolute pressure difference of each pressure gauge is greater than or equal to When the prediction result of the temperature and pressure balance model shows that the current temperature and pressure status is abnormal, an alarm will be triggered immediately and the event log will be recorded in the SCADA; Collect real-time data, clean and standardize the real-time data, and calculate the pressure difference to obtain the real-time pressure difference. , according to the real-time pressure difference and the threshold value for each pressure difference Calculate the deviation ratio; Set the deviation thresholds T1, T2 and T3, T1 <T2<T3; When T1<deviation ratio≤T2, it is judged as a slight abnormality; When T2<deviation ratio≤T3, it is judged as moderate abnormality; When T3<deviation ratio, it is judged as a serious abnormality.

6. A SCADA control system for producing natural gas from biogas based on temperature and pressure balance, based on the SCADA control method for producing natural gas from biogas based on temperature and pressure balance according to any one of claims 1 to 5, characterized in that: Including sensor module, data processing module, temperature and pressure balance model module, control module and abnormality detection module, The sensor module is used to monitor the temperature and pressure data in the biogas to natural gas process in real time through a temperature sensor and a pressure sensor; The data processing module is used to clean and standardize the collected temperature and pressure data, and also calculate the real-time pressure difference and compare it with the set threshold value; The temperature and pressure balance model module includes a linear regression model and an adaptive learning model, which respectively capture the linear and nonlinear relationships between temperature and pressure, and are used to combine the output of the model with the logistic regression model to construct a temperature and pressure balance model, predict the optimal temperature and pressure setting values ​​under the current environment, and calculate the optimal temperature setting value and pressure setting value according to the final predicted value; The control module is used to adjust the working states of the heater, cooler and pressure regulating valve in real time according to the predicted output of the temperature-pressure balance model; The anomaly detection module is used to monitor the temperature and pressure status of the system, define the pressure difference between the pressure sensors and set the threshold. When the system exceeds the set threshold, an alarm is triggered and an event log is recorded. Emergency measures are automatically taken according to the severity of the anomaly.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the SCADA control method for producing natural gas from biogas based on temperature and pressure balance according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the SCADA control method for producing natural gas from biogas based on temperature and pressure balance according to any one of claims 1 to 5 are implemented.

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